public void TestClassify()
{
SimpleWordsDataSource wds = new SimpleWordsDataSource();
BayesianClassifier classifier = new BayesianClassifier(wds);
string[] sentence = new string[] { "This", "is", "a", "sentence", "about", "java" };
Assert.AreEqual(IClassifierConstants.NEUTRAL_PROBABILITY, classifier.Classify(ICategorizedClassifierConstants.DEFAULT_CATEGORY, sentence), 0d);
wds.SetWordProbability(new WordProbability("This", .5d));
wds.SetWordProbability(new WordProbability("is", .5d));
wds.SetWordProbability(new WordProbability("a", .5d));
wds.SetWordProbability(new WordProbability("sentence", .2d));
wds.SetWordProbability(new WordProbability("about", .5d));
wds.SetWordProbability(new WordProbability("java", .99d));
Assert.AreEqual(.96d, classifier.Classify(ICategorizedClassifierConstants.DEFAULT_CATEGORY, sentence), .009d);
}
public void ClassifierTest()
{
var bc = new BayesianClassifier <int>();
bc.SetFeatureProbability(10, .50d);
bc.SetFeatureProbability(20, .2d);
bc.SetFeatureProbability(30, .50d);
bc.SetFeatureProbability(69, .99d);
var set = bc.Classify(new[] { 10, 20, 30, 69 });
Assert.NotNull(set);
Assert.AreEqual(1, set.Count);
var r = set.ElementAt(0);
Assert.AreEqual(.96d, r.Probability, .009d);
}
public void ClassifierTest() {
var bc = new BayesianClassifier<int>();
bc.SetFeatureProbability(10, .50d);
bc.SetFeatureProbability(20, .2d);
bc.SetFeatureProbability(30, .50d);
bc.SetFeatureProbability(69, .99d);
var set = bc.Classify(new[] { 10, 20, 30, 69 });
Assert.NotNull(set);
Assert.AreEqual(1, set.Count);
var r = set.ElementAt(0);
Assert.AreEqual(.96d, r.Probability, .009d);
}